Posts Tagged ‘ teaching ’

Stan without frontiers, Bayes without tears

April 24, 2017
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Stan without frontiers, Bayes without tears

This recent comment thread reminds me of a question that comes up from time to time, which is how to teach Bayesian statistics to students who aren’t comfortable with calculus. For continuous models, probabilities are integrals. And in just about every example except the one at 47:16 of this video, there are multiple parameters, so […] The post Stan without frontiers, Bayes without tears appeared first on Statistical Modeling, Causal…

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Graphs – beauty and truth

April 23, 2017
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Graphs – beauty and truth

Graphs – beauty and truth (with apologies to Keats) A good graph is elegant I really like graphs. I like the way graphs turn numbers into pictures. A good graph is elegant. It uses a few well-placed lines to communicate … Continue reading →

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Teaching Statistics: A Bag of Tricks (second edition)

April 20, 2017
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Teaching Statistics:  A Bag of Tricks (second edition)

Hey! Deb Nolan and I finished the second edition of our book, Teaching Statistics: A Bag of Tricks. You can pre-order it here. I love love love this book. As William Goldman would say, it’s the “good parts version”: all the fun stuff without the standard boring examples (counting colors of M&M’s, etc.). Great stuff […] The post Teaching Statistics: A Bag of Tricks (second edition) appeared first on Statistical…

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In Praise of T.A.s

April 18, 2017
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In Praise of T.A.s

With another teaching term completed, I'm reminded of how much we faculty members rely on our Teaching Assistants (T.A.s) This is especially true in the case of large undergraduate classes, where we'd be run off our feet without the invaluable input fr...

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Teaching pivot / un-pivot

April 11, 2017
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Teaching pivot / un-pivot

Authors: John Mount and Nina Zumel Introduction In teaching thinking in terms of coordinatized data we find the hardest operations to teach are joins and pivot. One thing we commented on is that moving data values into columns, or into a “thin” or entity/attribute/value form (often called “un-pivoting”, “stacking”, “melting” or “gathering“) is easy to … Continue reading Teaching pivot / un-pivot

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Mmore from Ppnas

April 10, 2017
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Kevin Lewis asks for my take on two new papers: Study 1: Honesty plays a key role in social and economic interactions and is crucial for societal functioning. However, breaches of honesty are pervasive and cause significant societal and economic problems that can affect entire nations. Despite its importance, remarkably little is known about the […] The post Mmore from Ppnas appeared first on Statistical Modeling, Causal Inference, and Social…

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My interview on EconTalk, and some other podcasts and videos

April 3, 2017
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My interview on EconTalk, and some other podcasts and videos

Russ Roberts recently interviewed me for his EconTalk podcast. We talked about social science and the garden of forking paths. Roberts was also going to talk with me about Case and Deaton, but we ran out of time. Whenever I announce a talk, people ask in comments if it will be streamed or recorded. Most […] The post My interview on EconTalk, and some other podcasts and videos appeared first…

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Coordinatized Data: A Fluid Data Specification

March 29, 2017
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Coordinatized Data: A Fluid Data Specification

Authors: John Mount and Nina Zumel. Introduction It has been our experience when teaching the data wrangling part of data science that students often have difficulty understanding the conversion to and from row-oriented and column-oriented data formats (what is commonly called pivoting and un-pivoting). Boris Artzybasheff illustration Real trust and understanding of this concept doesn’t … Continue reading Coordinatized Data: A Fluid Data Specification

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Some natural solutions to the p-value communication problem—and why they won’t work

March 21, 2017
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Blake McShane and David Gal recently wrote two articles (“Blinding us to the obvious? The effect of statistical training on the evaluation of evidence” and “Statistical significance and the dichotomization of evidence”) on the misunderstandings of p-values that are common even among supposed experts in statistics and applied social research. The key misconception has nothing […] The post Some natural solutions to the p-value communication problem—and why they won’t work…

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Ensemble Methods are Doomed to Fail in High Dimensions

March 15, 2017
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Ensemble Methods are Doomed to Fail in High Dimensions

Ensemble methods By ensemble methods, I (Bob, not Andrew) mean approaches that scatter points in parameter space and then make moves by inteprolating or extrapolating among subsets of them. Two prominent examples are: Ter Braak’s differential evolution   Goodman and Weare’s walkers There are extensions and computer implementations of these algorithms. For example, the Python […] The post Ensemble Methods are Doomed to Fail in High Dimensions appeared first on…

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